Google Certified Professional Data Engineer : Professional-Data-Engineer

Professional-Data-Engineer Exam Simulator
  • Exam Code: Professional-Data-Engineer
  • Exam Name: Google Certified Professional Data Engineer Exam
  • Updated: May 30, 2026
  • Q & A: 403 Questions and Answers

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This course will show you how to manage big data including loading, extracting, cleaning, and validating data. At the end of the training, you can easily create machine learning and statistical models as well as visualizing query results. This program is a bit lengthy but you have to practice well to get the knowledge needed on the actual exam. These are the following modules covered in the course:

  • Advanced BigQuery Performance and Functionality
  • Introduction to Processing Streaming Data
  • Serverless Data Processing with Cloud Dataflow
  • Serverless Messaging Using Cloud Sub/Pub
  • Custom Model building Using SQL in BigQuery ML
  • Prebuilt ML Models APIs for Unsaturated Data
  • Performing Spark on Cloud Dataproc
  • Creating a Data Lake
  • Introduction to Data Engineering
  • Bigtable Streaming Features and High-Throughput BigQuery
  • Big Data Analytics with Cloud Al Platform Notebook
  • Production ML Pipelines and use of Kubeflow
  • Building a Data Warehouse
  • Cloud Dataflow Streaming Features
  • Handling Data Pipelines with Cloud Composer and Cloud Data Fusion
  • Introduction to Building Batch Data Pipelines
  • Custom Model building Utilizing Cloud AutoML

These modules involve everything the candidate requires for passing the Professional Data Engineer certification exam. Thus, you will not miss anything if you are taking this learning program keenly and apply the required knowledge in an appropriate way. You would end up getting a good score and achieving the Google Professional Data Engineer certification.

Career Opportunities

The certified individuals can explore a variety of job opportunities. Some of the positions that they can take up include a Software Engineer, a Cloud Architect, a Data Engineer, a Sales Engineer, a Data Scientist, a Cloud Developer, and a Kubernetes Architect, among others. The salary outlook for these job roles is an average of $128,500 per annum.

Google Professional-Data-Engineer Exam Syllabus Topics:

TopicDetails
Topic 1
  • Ingesting and processing the data: The topic discusses planning of the data pipelines, building the pipelines, acquisition and import of data, and deploying and operationalizing the pipelines.
Topic 2
  • Storing the data: This topic explains how to select storage systems and how to plan using a data warehouse. Additionally, it discusses how to design for a data mesh.
Topic 3
  • Preparing and using data for analysis: Questions about data for visualization, data sharing, and assessment of data may appear.
Topic 4
  • Designing data processing systems: It delves into designing for security and compliance, reliability and fidelity, flexibility and portability, and data migrations.
Topic 5
  • Maintaining and automating data workloads: It discusses optimizing resources, automation and repeatability design, and organization of workloads as per business requirements. Lastly, the topic explains monitoring and troubleshooting processes and maintaining awareness of failures.

Reference: https://cloud.google.com/certification/data-engineer

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